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National Chung Hsing University Institutional Repository - NCHUIR > 工學院 > 電機工程學系所 > 依資料類型分類 > 期刊論文 >  3D reconstruction and face recognition using kernel-based ICA and neural networks

Please use this identifier to cite or link to this item: http://nchuir.lib.nchu.edu.tw/handle/309270000/134901

標題: 3D reconstruction and face recognition using kernel-based ICA and neural networks
作者: Kuo, S.C.;Lin, C.J.;Liao, J.R.
日期: 2011
Issue Date: 2012-12-14 11:12:12 (UTC+8)
關連: Expert Systems with Applications, Volume 38, Issue 5, Page(s) 5406-5415.
摘要: Kernel-based nonlinear characteristic extraction and classification algorithms are popular new research directions in machine learning. In this paper, we propose an improved photometric stereo scheme based on improved kernel-independent component analysis method to reconstruct 3D human faces. Next, we fetch the information of 3D faces for facial face recognition. For reconstruction, we obtain the correct normal vector's sequence to form the surface, and use a method for enforcing integrability to reconstruct 3D objects. We test our algorithm on a number of real images captured from the Yale Face Database B. and use three kinds of methods to fetch characteristic values. Those methods are called contour-based, circle-based, and feature-based methods. Then, a three-layer, feed-forward neural network trained by a back-propagation algorithm is used to realize a classifier. All the experimental results were compared to those of the existing human face reconstruction and recognition approaches tested on the same images. The experimental results demonstrate that the proposed improved kernel independent component analysis (IKICA) method is efficient in reconstruction and face recognition applications. (C) 2010 Elsevier Ltd. All rights reserved.
Relation: Expert Systems with Applications
Appears in Collections:[依教師分類] 廖俊睿
[依資料類型分類] 期刊論文
[依教師分類] 廖俊睿

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